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The purpose of this work was to obtain a detailed comparison of engine performance and exhaust emissions from compressed natural gas and gasoline fueled Spark Ignition (SI) engines. This research deals with a quasi-dimensional, two-zone, thermodynamic simulation of four-stroke SI engine fueled with a wide range of liquid and gaseous fuels. The results show that the power output of the engine was reduced when fueled by natural gas due to its low volumetric efficiency, but both fuels exhibited nearly equal thermal efficiency. Significant lowering of flame propagation rates with the lower hydrocarbons (methane, ethane, propane) of natural gas fueled spark ignition engine is observed with the corresponding increases in the average length of the combustion duration and ignition delay times. The validity of the model has been carried out with reliable data obtained under same engine setup and yields satisfactory agreement with the corresponding predicted values.

The objective of this paper is the prediction of efficiency and NOx emission of a Spark Ignition engine based on engine design and operational parameters using artificial neural networks (ANN). This paper deals with quasi-dimensional, two-zone thermodynamic simulation of four-stroke SI engine fueled with biogas. The developed computer model has been used for the prediction of the combustion and emission characteristics of biogas in SI engines. Predicted results indicate that the presence of carbon dioxide can reduce oxides of nitrogen (NOx) emissions, but since lower cylinder pressures result, engine power and thermal efficiency are reduced. This is mainly due to the lower heating value of biogas. Using the results from this program, the effects of operational and design parameters of the engine were investigated. For real time computations in electronic control unit (ECU) an artificial neural network (ANN) model has been suggested as an alternative to the engine simulation model.

Current generation of metal monolith using binary catalysts Pt/Rh (5:1) is simulated for transient temperature and conversion inside a catalytic converter during warm-up. A new concept in mass transfer on a catalytic combustion is introduced in this model for improving accuracy is known as Reynolds analogy. Design parameters and operating conditions are investigated for its influence on solid temperature and conversion of species. New patterns of precious metal loading have been investigated for metal savings and maximum conversion efficiency. Satisfactory validation of computed data was observed.

In this research, the potential of Diethyl ether (DEE) which is a renewable bio-based fuel has been identified as a supplementary oxygenated additive to improve fuel properties and combustion characteristics of biodiesel (Karanja oil methyl ester - KOME) like its high viscosity, cold starting problems and a high level of NOx emissions through an experimental investigation. The tests were conducted on a single cylinder DI diesel engine fueled with neat KOME as a base fuel and blends of 5, 10, 15 and 20% DEE on a volume basis. Some physicochemical properties of test fuels such as heating value, viscosity, specific gravity and distillation profile were determined in accordance to the ASTM standards. The results obtained from the engine tests have shown a significant reduction in NOx emissions especially for DEE addition of more than 10% on a volume basis and a little decrease in smoke of DEE blends compared with neat KOME.